Coverage for python/lsst/daf/butler/formatters/yaml.py : 28%

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1# This file is part of daf_butler.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (http://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the GNU General Public License
20# along with this program. If not, see <http://www.gnu.org/licenses/>.
22from __future__ import annotations
24__all__ = ("YamlFormatter", )
26import builtins
27import yaml
28import dataclasses
30from typing import (
31 TYPE_CHECKING,
32 Any,
33 Optional,
34 Type,
35)
37from .file import FileFormatter
39if TYPE_CHECKING: 39 ↛ 40line 39 didn't jump to line 40, because the condition on line 39 was never true
40 from lsst.daf.butler import StorageClass
43class YamlFormatter(FileFormatter):
44 """Interface for reading and writing Python objects to and from YAML files.
45 """
46 extension = ".yaml"
48 unsupportedParameters = None
49 """This formatter does not support any parameters"""
51 supportedWriteParameters = frozenset({"unsafe_dump"})
52 """Allow the normal yaml.dump to be used to write the YAML. Use this
53 if you know that your class has registered representers."""
55 def _readFile(self, path: str, pytype: Type[Any] = None) -> Any:
56 """Read a file from the path in YAML format.
58 Parameters
59 ----------
60 path : `str`
61 Path to use to open YAML format file.
62 pytype : `class`, optional
63 Not used by this implementation.
65 Returns
66 -------
67 data : `object`
68 Either data as Python object read from YAML file, or None
69 if the file could not be opened.
71 Notes
72 -----
73 The `~yaml.SafeLoader` is used when parsing the YAML file.
74 """
75 try:
76 with open(path, "rb") as fd:
77 data = self._fromBytes(fd.read(), pytype)
78 except FileNotFoundError:
79 data = None
81 return data
83 def _fromBytes(self, serializedDataset: bytes, pytype: Optional[Type[Any]] = None) -> Any:
84 """Read the bytes object as a python object.
86 Parameters
87 ----------
88 serializedDataset : `bytes`
89 Bytes object to unserialize.
90 pytype : `class`, optional
91 Not used by this implementation.
93 Returns
94 -------
95 inMemoryDataset : `object`
96 The requested data as an object, or None if the string could
97 not be read.
99 Notes
100 -----
101 The `~yaml.SafeLoader` is used when parsing the YAML.
102 """
103 data = yaml.safe_load(serializedDataset)
105 try:
106 data = data.exportAsDict()
107 except AttributeError:
108 pass
109 return data
111 def _writeFile(self, inMemoryDataset: Any) -> None:
112 """Write the in memory dataset to file on disk.
114 Will look for `_asdict()` method to aid YAML serialization, following
115 the approach of the simplejson module. The `dict` will be passed
116 to the relevant constructor on read.
118 Parameters
119 ----------
120 inMemoryDataset : `object`
121 Object to serialize.
123 Raises
124 ------
125 Exception
126 The file could not be written.
128 Notes
129 -----
130 The `~yaml.SafeDumper` is used when generating the YAML serialization.
131 This will fail for data structures that have complex python classes
132 without a registered YAML representer.
133 """
134 self.fileDescriptor.location.uri.write(self._toBytes(inMemoryDataset))
136 def _toBytes(self, inMemoryDataset: Any) -> bytes:
137 """Write the in memory dataset to a bytestring.
139 Will look for `_asdict()` method to aid YAML serialization, following
140 the approach of the simplejson module. The `dict` will be passed
141 to the relevant constructor on read.
143 Parameters
144 ----------
145 inMemoryDataset : `object`
146 Object to serialize
148 Returns
149 -------
150 serializedDataset : `bytes`
151 YAML string encoded to bytes.
153 Raises
154 ------
155 Exception
156 The object could not be serialized.
158 Notes
159 -----
160 The `~yaml.SafeDumper` is used when generating the YAML serialization.
161 This will fail for data structures that have complex python classes
162 without a registered YAML representer.
163 """
164 if dataclasses.is_dataclass(inMemoryDataset):
165 inMemoryDataset = dataclasses.asdict(inMemoryDataset)
166 elif hasattr(inMemoryDataset, "_asdict"):
167 inMemoryDataset = inMemoryDataset._asdict()
168 unsafe_dump = self.writeParameters.get("unsafe_dump", False)
169 if unsafe_dump:
170 serialized = yaml.dump(inMemoryDataset)
171 else:
172 serialized = yaml.safe_dump(inMemoryDataset)
173 return serialized.encode()
175 def _coerceType(self, inMemoryDataset: Any, storageClass: StorageClass,
176 pytype: Optional[Type[Any]] = None) -> Any:
177 """Coerce the supplied inMemoryDataset to type `pytype`.
179 Parameters
180 ----------
181 inMemoryDataset : `object`
182 Object to coerce to expected type.
183 storageClass : `StorageClass`
184 StorageClass associated with `inMemoryDataset`.
185 pytype : `type`, optional
186 Override type to use for conversion.
188 Returns
189 -------
190 inMemoryDataset : `object`
191 Object of expected type `pytype`.
192 """
193 if inMemoryDataset is not None and pytype is not None and not hasattr(builtins, pytype.__name__):
194 if storageClass.isComposite():
195 inMemoryDataset = storageClass.delegate().assemble(inMemoryDataset, pytype=pytype)
196 elif not isinstance(inMemoryDataset, pytype):
197 if dataclasses.is_dataclass(pytype):
198 # dataclasses accept key/value parameters
199 inMemoryDataset = pytype(**inMemoryDataset)
200 else:
201 # Hope that we can pass the arguments in directly
202 inMemoryDataset = pytype(inMemoryDataset)
203 return inMemoryDataset